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        <h1 id="python中的WFDB库使用"><a href="#python中的WFDB库使用" class="headerlink" title="python中的WFDB库使用"></a>python中的WFDB库使用</h1><h2 id="1-获取MIT——PhysioNet数据库的所有库名称"><a href="#1-获取MIT——PhysioNet数据库的所有库名称" class="headerlink" title="1.获取MIT——PhysioNet数据库的所有库名称"></a>1.获取MIT——PhysioNet数据库的所有库名称</h2><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> wfdb <span class="keyword">as</span> wfdb</span><br><span class="line"></span><br><span class="line">dbs = wfdb.get_dbs()</span><br><span class="line">print(dbs)</span><br></pre></td></tr></table></figure>

<p>获取PhysioNet所有库的名称列表：</p>
<p>[[‘adfecgdb’, ‘Abdominal and Direct Fetal ECG Database’], [‘aftdb’, ‘AF Termination Challenge Database’], [‘ahadb’, ‘AHA Database [sample excluded record]’], [‘aami-ec13’, ‘ANSI/AAMI EC13 Test Waveforms’], [‘apnea-ecg’, ‘Apnea-ECG Database’], [‘chfdb’, ‘BIDMC Congestive Heart Failure Database’], [‘bidmc’, ‘BIDMC PPG and Respiration Dataset’], [‘bpssrat’, ‘Blood Pressure in Salt-Sensitive Dahl Rats’], [‘capslpdb’, ‘CAP Sleep Database’], [‘crisdb’, ‘CAST RR Interval Sub-Study Database’], [‘cves’, ‘Cerebral Vasoregulation in Elderly with Stroke’], [‘challenge/2009/test-set-a’, ‘Challenge 2009 Test Set A’], [‘challenge/2009/test-set-b’, ‘Challenge 2009 Test Set B’], [‘challenge/2010/set-a’, ‘Challenge 2010 Training Set A’], [‘challenge/2010/set-b’, ‘Challenge 2010 Test Set B’], [‘challenge/2010/set-c’, ‘Challenge 2010 Test Set C’], [‘challenge/2011/sim’, ‘Challenge 2011 Pilot Set’], [‘challenge/2011/set-a’, ‘Challenge 2011 Training Set A’], [‘challenge/2011/set-b’, ‘Challenge 2011 Test Set B’], [‘challenge/2013/set-a’, ‘Challenge 2013 Training Set A’], [‘challenge/2013/set-b’, ‘Challenge 2013 Test Set B’], [‘challenge/2014/set-p2’, ‘Challenge 2014 Extended Training Set’], [‘challenge/2014/set-p’, ‘Challenge 2014 Training Set’], [‘challenge/2015/training’, ‘Challenge 2015 Training Set’], [‘challenge/2016/training-a’, ‘Challenge 2016 Training Set A’], [‘challenge/2016/training-b’, ‘Challenge 2016 Training Set B’], [‘challenge/2016/training-c’, ‘Challenge 2016 Training Set C’], [‘challenge/2016/training-d’, ‘Challenge 2016 Training Set D’], [‘challenge/2016/training-e’, ‘Challenge 2016 Training Set E’], [‘challenge/2016/training-f’, ‘Challenge 2016 Training Set F’], [‘challenge/2017/training’, ‘Challenge 2017 Training Set’], [‘challenge/2018/training’, ‘Challenge 2018 Training Set’], [‘challenge/2018/test’, ‘Challenge 2018 Test Set’], [‘charisdb’, ‘CHARIS database’], [‘chbmit’, ‘CHB-MIT Scalp EEG Database’], [‘cebsdb’, ‘Combined measurement of ECG, Breathing and Seismocardiograms’], [‘culm’, ‘Complex Upper-Limb Movements’], [‘chf2db’, ‘Congestive Heart Failure RR Interval Database’], [‘ctu-uhb-ctgdb’, ‘CTU-CHB Intrapartum Cardiotocography Database’], [‘cudb’, ‘CU Ventricular Tachyarrhythmia Database’], [‘ecgdmmld’, ‘ECG Effects of Dofetilide, Moxifloxacin, Dofetilide+Mexiletine, Dofetilide+Lidocaine and Moxifloxacin+Diltiazem’], [‘ecgcipa’, ‘CiPA ECG Validation Study’], [‘ecgrdvq’, ‘ECG Effects of Ranolazine, Dofetilide, Verapamil, and Quinidine’], [‘ecgiddb’, ‘ECG-ID Database’], [‘eegmat’, ‘EEG During Mental Arithmetic Tasks’], [‘eegmmidb’, ‘EEG Motor Movement/Imagery Dataset’], [‘ltrsvp’, ‘EEG Signals from an RSVP Task’], [‘erpbci’, ‘ERP-based Brain-Computer Interface recordings’], [‘edb’, ‘European ST-T Database’], [‘earh’, ‘Evoked Auditory Responses in Heading Impaired’], [‘earndb’, ‘Evoked Auditory Responses in Normals’], [‘emgdb’, ‘Examples of Electromyograms’], [‘fantasia’, ‘Fantasia Database’], [‘fecgsyndb’, ‘Fetal ECG Synthetic Database’], [‘fpcgdb’, ‘Fetal PCG Database’], [‘gaitdb’, ‘Gait in Aging and Disease Database’], [‘gaitndd’, ‘Gait in Neurodegenerative Disease Database’], [‘gait-maturation-db/data’, ‘Gait Maturation Database’], [‘meditation/data’, ‘Heart Rate Oscillations during Meditation’], [‘hbedb’, ‘Human Balance Evaluation Database’], [‘ehgdb’, ‘Icelandic 16-electrode Electrohysterogram Database’], [‘iafdb’, ‘Intracardiac Atrial Fibrillation Database’], [‘ltafdb’, ‘Long Term AF Database’], [‘ltstdb’, ‘Long Term ST Database’], [‘mssvepdb’, ‘MAMEM SSVEP Database’], [‘mghdb’, ‘MGH/MF Waveform Database’], [‘mimicdb’, ‘MIMIC Database’], [‘mimicdb/numerics’, ‘MIMIC Database Numerics’], [‘mimic2cdb’, ‘MIMIC II Clinical Database Public Subset’], [‘mimic2wdb/30’, ‘MIMIC II/III Waveform Database, part 0’], [‘mimic2wdb/31’, ‘MIMIC II/III Waveform Database, part 1’], [‘mimic2wdb/32’, ‘MIMIC II/III Waveform Database, part 2’], [‘mimic2wdb/33’, ‘MIMIC II/III Waveform Database, part 3’], [‘mimic2wdb/34’, ‘MIMIC II/III Waveform Database, part 4’], [‘mimic2wdb/35’, ‘MIMIC II/III Waveform Database, part 5’], [‘mimic2wdb/36’, ‘MIMIC II/III Waveform Database, part 6’], [‘mimic2wdb/37’, ‘MIMIC II/III Waveform Database, part 7’], [‘mimic2wdb/38’, ‘MIMIC II/III Waveform Database, part 8’], [‘mimic2wdb/39’, ‘MIMIC II/III Waveform Database, part 9’], [‘mimic2wdb/matched’, ‘MIMIC II Waveform Database Matched Subset’], [‘mimic3wdb/matched’, ‘MIMIC III Waveform Database Matched Subset’], [‘mitdb’, ‘MIT-BIH Arrhythmia Database’], [‘pwave’, ‘MIT-BIH Arrhythmia Database P-Wave Annotations’], [‘afdb’, ‘MIT-BIH Atrial Fibrillation Database’], [‘cdb’, ‘MIT-BIH ECG Compression Test Database’], [‘ltdb’, ‘MIT-BIH Long-Term ECG Database’], [‘vfdb’, ‘MIT-BIH Malignant Ventricular Ectopy Database’], [‘nstdb’, ‘MIT-BIH Noise Stress Test Database’], [‘nsrdb’, ‘MIT-BIH Normal Sinus Rhythm Database’], [‘excluded’, ‘… [Recordings excluded from the NSR DB]’], [‘slpdb’, ‘MIT-BIH Polysomnographic Database’], [‘stdb’, ‘MIT-BIH ST Change Database’], [‘svdb’, ‘MIT-BIH Supraventricular Arrhythmia Database’], [‘mmgdb’, ‘MMG Database’], [‘macecgdb’, ‘Motion Artifact Contaminated ECG Database’], [‘motion-artifact’, ‘Motion Artifact Contaminated fNIRS and EEG Data’], [‘noneeg’, ‘Non-EEG Dataset for Assessment of Neurological Status’], [‘nifecgdb’, ‘Non-Invasive Fetal ECG Database’], [‘nifeadb’, ‘Non-Invasive Fetal ECG Arrhythmia Database’], [‘nsr2db’, ‘Normal Sinus Rhythm RR Interval Database’], [‘ob1db’, ‘OB-1 Fetal ECG Database [sample record]’], [‘afpdb’, ‘PAF Prediction Challenge Database’], [‘osv’, ‘Pattern Analysis of Oxygen Saturation Variability’], [‘prcp’, ‘Physiologic Response to Changes in Posture’], [‘szdb’, ‘Post-Ictal Heart Rate Oscillations in Partial Epilepsy’], [‘picsdb’, ‘Preterm Infant Cardio-Respiratory Signals Database’], [‘ptbdb’, ‘PTB Diagnostic ECG Database’], [‘qtdb’, ‘QT Database’], [‘rvmh1’, ‘Response to Valsalva Maneuver in Humans’], [‘sufhsdb’, ‘Shiraz University Fetal Heart Sounds Database’], [‘simfpcgdb’, ‘Simulated Fetal Phonocardiograms’], [‘sleepbrl’, ‘Sleep Bioradiolocation Database’], [‘sleep-edfx’, ‘Sleep-EDF Database [Expanded]’], [‘shhpsgdb’, ‘Sleep Heart Health Study PSG Database [sample record]’], [‘shareedb’, ‘Smart Health for Assessing the Risk of Events via ECG Database’], [‘mvtdb/data’, ‘Spontaneous Ventricular Tachyarrhythmia Database’], [‘sgamp’, ‘Squid Giant Axon Membrane Potential’], [‘incartdb’, ‘St Petersburg INCART 12-lead Arrhythmia Database’], [‘staffiii’, ‘STAFF III Database’], [‘drivedb’, ‘Stress Recognition in Automobile Drivers’], [‘sddb’, ‘Sudden Cardiac Death Holter Database’], [‘twadb’, ‘T-Wave Alternans Challenge Database’], [‘taichidb’, ‘Tai Chi, Physiological Complexity, and Healthy Aging - Gait’], [‘tpehgdb’, ‘Term-Preterm EHG Database’], [‘tpehgt’, ‘Term-Preterm EHG DataSet with Tocogram (TPEHGT DS)’], [‘ucddb’, ‘UCD Sleep Apnea Database’], [‘unicaprop’, ‘UniCA ElectroTastegram Database (PROP)’], [‘videopulse’, ‘Video Pulse Signals in Stationary and Motion Conditions’], [‘voiced’, ‘VOice ICar fEDerico II Database’], [‘wrist’, ‘Wrist PPG During Exercise’], [‘mimic2db’, ‘MIMIC II Waveform DB, v2 [deprecated, use v3]’], [‘mimic2db/numerics’, ‘MIMIC II Waveform DB, v2 Numerics [deprecated, use v3]’], [‘sleep-edf’, ‘Sleep-EDF Database, v1 [deprecated, use sleep-edfx]’]]</p>
<p>这个列表其实在网站*<a target="_blank" rel="noopener" href="https://physionet.org/physiobank/database/*%E4%B8%AD%E4%B9%9F%E5%8F%AF%E4%BB%A5%E6%9F%A5%E7%9C%8B%E6%9F%A5%E7%9C%8B">https://physionet.org/physiobank/database/*中也可以查看查看</a></p>
<p><strong>找到想要分析的睡眠数据库：</strong></p>
<p> <strong>[‘slpdb’, ‘MIT-BIH Polysomnographic Database’]</strong></p>
<h2 id="2-获取想要的睡眠数据库的所有信号记录列表"><a href="#2-获取想要的睡眠数据库的所有信号记录列表" class="headerlink" title="2.获取想要的睡眠数据库的所有信号记录列表"></a>2.获取想要的睡眠数据库的所有信号记录列表</h2><p>由第一个库知道， <strong>[‘slpdb’, ‘MIT-BIH Polysomnographic Database’]**，对应的数据库就为</strong>slpdb**，获取里面所有数据集的列表：</p>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line">recs_list = wfdb.get_record_list(<span class="string">&#x27;slpdb&#x27;</span>)</span><br><span class="line">print(recs_list)</span><br></pre></td></tr></table></figure>

<p>[‘slp01a’, ‘slp01b’, ‘slp02a’, ‘slp02b’, ‘slp03’, ‘slp04’, ‘slp14’, ‘slp16’, ‘slp32’, ‘slp37’, ‘slp41’, ‘slp45’, ‘slp48’, ‘slp59’, ‘slp60’, ‘slp61’, ‘slp66’, ‘slp67x’]</p>
<h2 id="3-获取对应的数据库里面的内容"><a href="#3-获取对应的数据库里面的内容" class="headerlink" title="3.获取对应的数据库里面的内容"></a>3.获取对应的数据库里面的内容</h2>
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